| 光谱学与光谱分析 |
|
|
|
|
|
| Observation and Simulation of Bi-Directional Spectral Reflectance on Different Type of Soils |
| CHENG Jie-liang,SHI Zhou*,LI Hong-yi |
| Institute of Agricultural Remote Sensing and Information System, Zhejiang University, Hangzhou 310029, China |
|
|
|
|
Abstract Knowledge of radiative transfer over bare soils is a prerequisite to addressing vegetation canopies and predicting soil properties by remote sensing. In the present study, the change in the spectral reflectance for three soils (i. e. red soil, paddy soil and coastal saline soil) with different view zenith and azimuth angles in the visible band (620 nm) and Landsat TM4 near infrared wavebands (760-900 nm) was measured in laboratory. The results showed that soil reflectance increased with increasing off-nadir view angle for all azimuth directions and soil bidirectional reflectance was azimuthally symmetric. The reflectance was highest in backscattering direction and lowest in forward-scattering direction. The bidirectional reflectance was simulated well using the Hapke model derived from the radiative transfer theory. The root mean square errors (RMSE) were 0.003, 0.002 and 0.004 and the correlation coefficients were 0.995, 0.998 and 0.998 in simulating bidirectional reflectance in visible wavebands for red soil, paddy soil and coastal saline soil, respectively; RMSE were 0.004, 0.006 and 0.005 and the correlation coefficients were 0.997, 0.996 and 0.998 in simulating bidirectional reflectance in NIR wavebands for these soils, respectively. It is stated clearly that Hapke model could be used to simulate the whole spectra curve, then to retrieve the soil surface characteristics.
|
|
Received: 2007-01-28
Accepted: 2007-05-06
|
|
|
|
Corresponding Authors:
SHI Zhou
E-mail: shizhou@zju.edu.cn
|
|
[1] LI Xiao-wen（李小文）. Remote Sensing of Environment China（环境遥感），1989, 4（1）: 67.
[2] Alfredo R H. Photo-Interpretation, 1996, 2: 101.
[3] Jacquemoud S, Baret F, Hanocq J F. Remote Sensing of Environment, 1992, 41: 123.
[4] Pinty B, Verstraete M M, Dickinson R E. Remote Sensing of Environment, 1989, 27: 273.
[5] Chappell A, Zobeck T M, Brunner G. Remote Sensing of Environment, 2006, 102: 328.
[6] Chappell A, Strong C, McTainsh G, et al. Remote Sensing of Environment, 2007, 106: 508.
[7] Hapke B W. Theory. Journal of Geophysical Research, 1981, 86: 3039.
[8] Hapke B W. Icarus, 1984, 59: 41.
[9] Hapke B W. Icarus, 1986, 67: 264.
[10] Liang S, Townshend J R G. Remote Sensing of Environment, 1996, 55: 1.
[11] Henderson T L, Baumgardner M F, Franzmeier D P, et al. Soil Sci. Soc. Am. J., 1992, 56(3): 865.
[12] SHI Zhou, CHENG Jie-Liang, HUANG Ming-Xiang, et al. Pedosphere, 2006, 16(2): 154.
[13] Drake H R. Int. J. Remote Sensing, 1995, 16: 2555.
[14] Ben-Dor E, Banin A. Soil Sci. Soc. Am. J., 1995, 59: 364.
[15] SUN Jian-ying, LI Min-zan, ZHENG Li-hua, et al（孙建英，李民赞，郑立华，等）. Spectroscopy and Spectral Analysis（光谱学与光谱分析）, 2006, 26（3）: 426.
[16] Torrent J, Schwertmann H, Alferez F. Soil Science, 1983, 13: 354.
[17] Dalal R C, Henry R J. Soil Sci. Soc. Am. J, 1985, 50(1): 120.
[18] Krishanan P, Alexander J D, Butler B J, et al. Soil Sci. Soc. Am. J., 1980, 44: 1282.
[19] DENG Ru-ru, TIAN Guo-liang, LIU Qin-huo, et al（邓孺孺，田国良，柳钦火，等）. Journal of Remote Sensing（遥感学报），2004, 8(1): 75. |
| [1] |
XU Tian1, 2, LI Jing1, 2, LIU Zhen-hua1, 2*. Remote Sensing Inversion of Soil Manganese in Nanchuan District, Chongqing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 69-75. |
| [2] |
LI Hu1, ZHONG Yun1, 2, FENG Ya-ting1, LIN Zhen1, ZHU Shi-jiang1, 2*. Multi-Vegetation Index Soil Moisture Inversion Model Based on UAV
Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 207-214. |
| [3] |
HAN Xue1, 2, LIU Hai1, 2, LIU Jia-wei3, WU Ming-kai1, 2*. Rapid Identification of Inorganic Elements in Understory Soils in
Different Regions of Guizhou Province by X-Ray
Fluorescence Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 225-229. |
| [4] |
MENG Shan1, 2, LI Xin-guo1, 2*. Estimation of Surface Soil Organic Carbon Content in Lakeside Oasis Based on Hyperspectral Wavelet Energy Feature Vector[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3853-3861. |
| [5] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
| [6] |
CHENG Gang1, CAO Ya-nan1, TIAN Xing1, CAO Yuan2, LIU Kun2. Simulation of Airflow Performance and Parameter Optimization of
Photoacoustic Cell Based on Orthogonal Test[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3899-3905. |
| [7] |
FU Wen-xiang, DONG Li-qiang, YANG Liu*. Research Progress on Detection of Chemical Warfare Agent Simulants and Toxic Gases by Photoacoustic Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3653-3658. |
| [8] |
CHENG Hui-zhu1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, MA Qian1, 2, ZHAO Yan-chun1, 2. Genetic Algorithm Optimized BP Neural Network for Quantitative
Analysis of Soil Heavy Metals in XRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3742-3746. |
| [9] |
XIE Peng, WANG Zheng-hai*, XIAO Bei, CAO Hai-ling, HUANG Yi, SU Wen-lin. Hyperspectral Quantitative Inversion of Soil Selenium Content Based on sCARS-PSO-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3599-3606. |
| [10] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [11] |
CHEN Hao1, 2, WANG Hao3*, HAN Wei3, GU Song-yan4, ZHANG Peng4, KANG Zhi-ming1. Impact Analysis of Microwave Real Spectral Response on Rapid Radiance Simulation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3260-3265. |
| [12] |
AN Bai-song1, 2, WANG Xue-mei1, 2*, HUANG Xiao-yu1, 2, KAWUQIATI Bai-shan1, 2. Hyperspectral Estimation of Soil Lead Content Based on Random Frog Band Selection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3302-3309. |
| [13] |
LIU Wen-bo, LIU Jin, HAN Tong-shuai*, GE Qing, LIU Rong. Simulation of the Effect of Dermal Thickness on Non-Invasive Blood Glucose Measurement by Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2699-2704. |
| [14] |
DENG Yun1, 2, NIU Zhao-wen1, 2, FENG Qi-yao1, 2, WANG Yu1, 2*. A Novel Hyperspectral Prediction Model of Organic Matter in Red Soil Based on Improved Temporal Convolutional Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2942-2951. |
| [15] |
CAI Hai-hui1, ZHOU Ling2, SHI Zhou3, JI Wen-jun4, LUO De-fang1, PENG Jie1, FENG Chun-hui5*. Hyperspectral Inversion of Soil Organic Matter in Jujube Orchard
in Southern Xinjiang Using CARS-BPNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2568-2573. |
|
|
|
|
